Multiple factors play important roles in the susceptibility of individuals to develop mental disorders, with identification of underlying etiologic mechanisms contingent on clarification of genetic and environmental contributions to familial aggregation. Quantitative traits correlated with liability to affection provide much greater information content than groupings of individuals into affected or unaffected classes, and it is therefore desirable to cojointly analyze both sources of data. The aim of the proposed study is to develop and evaluate powerful new bivariate methods for investigating psychiatric and other non-Mendelian familial illnesses. Application of bivariate methods can increase the power of genetic analysis for resolving a major gene effect through segregation analysis, for identifying individuals that fall within a spectrum of illnesses related to a "core" disease phenotype, for improving the accuracy of risk estimation, and for resolving clinical heterogeneity and biological subtypes. In the first phase of the proposed study, a generalized bivariate model will be developed that allows co-segregation of a disease and a quantitative trait through common environment, polygenes, and one or two major loci. Theoretical issues related to adaptation of Monte Carlo methods to allow for sampling from the distribution of all possible major-genotype configurations and development of approximations of probabilities associated with multivariate normal integrals will allow resolution of computational problems in the bivariate analysis of multigenerational pedigrees. The probability of genetic recombination occurring between two loci will be modelled, allowing for (a) determination of whether the disease and the correlated trait are transmitted through the same, independent, or linked major loci and (b) direct incorporation of genetic marker data in bivariate analyses. In the second stage, a systematic, comprehensive set of computer simulation experiments will be performed to assess the power, robustness, and operating characteristics of the new bivariate methods as compared to pre-existing approaches. In the third stage, schizophrenic probands and their relatives will be assessed with standardized diagnostic instruments. All subjects will be tested with the Continuous Performance Test and the Minnesota Multiphasic Personality Inventory in order to obtain quantitative measures of attentional dysfunction and psychometric deviance. The methods developed will then be applied to investigate the familial coaggregation of schizophrenia with the two traits.